文章基本信息

标题：On Synchronous Binary Log-Linear Learning and Second Order Q-learning * * This work was supported by an NSERC grant.
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作者：Mohammadhosein Hasanbeig ; Lacra Pavel
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：8987-8992
DOI：10.1016/j.ifacol.2017.08.1326
语种：English
出版社：Elsevier
摘要：AbstractThe focus of this paper is on the enhancement of Log Linear Learning (LLL) and Q-learning (QL) in game theory and their applications in multi-robot control. We first propose a modified Binary Log-Linear Learning (BLLL) algorithm that can achieve a better performance and higher learning rate when is compared to standard BLLL. However, due to a number of assumptions, practical applicability of a LLL-based algorithm is limited. To relax this limitation we then propose a modified QL algorithm that can achieve the same performance but with the price of lower learning rate. The algorithms proposed are tested numerically.